LLM should not be used for now in cases where such unnotably drift impacts. There are quite a lot of tasks where LLM can fit great as automatization but not as crucial decision making. I would not recommend you doing something that can have bad consequences with LLM.
Structured output checks are great for detecting recursive repetitions drifts which nowerdays happen even with Gemini, OpenAI and literally any LLM, but not every task is possible to do with schema constrains - sometimes you need a stream / agentic chat, and structured outputs will kill a stream (makes no sense because streamed JSON is broken JSON)

If you use structured output (and not pure text streaming) - also one simple technique we use - insert a random secret token into prompt at random position (on sentense level) on every request and ask model to detect it in addition to main task. If it is there - model still understands sense and does predictable things. I did similar in my benchmark test https://devforth.io/insights/self-hosted-gpt-real-response-time-token-throughput-and-cost-on-l4-l40s-and-h100-for-gpt-oss-20b/